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The significance of air pollution and the problems associated with it are fueling deployments of air quality monitoring stations worldwide. The most common approach for air quality monitoring is to rely on environmental monitoring stations,…

Signal Processing · Electrical Eng. & Systems 2021-01-26 Francesco Concas , Julien Mineraud , Eemil Lagerspetz , Samu Varjonen , Xiaoli Liu , Kai Puolamäki , Petteri Nurmi , Sasu Tarkoma

The development of low-cost sensors and novel calibration algorithms offer new opportunities to supplement existing regulatory networks to measure air pollutants at a high spatial resolution and at hourly and sub-hourly timescales. We use a…

Low-cost particulate matter (PM) sensors have become increasingly popular due to their compact size, low power consumption, and cost-effective installation and maintenance. While several studies have explored the effects of meteorological…

Systems and Control · Electrical Eng. & Systems 2025-04-10 Gulshan Kumar , Prasannaa Kumar D , Jay Dhariwal , Seshan Srirangarajan

Data collection in economically constrained countries often necessitates using approximate and biased measurements due to the low-cost of the sensors used. This leads to potentially invalid predictions and poor policies or decision making.…

Machine Learning · Computer Science 2019-12-02 Michael T. Smith , Joel Ssematimba , Mauricio A. Alvarez , Engineer Bainomugisha

Air pollution remains a major global issue that seriously impacts public health, environmental quality, and ultimately human health. To help monitor problem, we have created and constructed a low-cost, real-time, portable air quality…

Signal Processing · Electrical Eng. & Systems 2025-07-01 S M Minhazur Rahman , Md. Amrin Ibna Hasnath , Rifatul Islam , Ahmed Faizul Haque Dhrubo , Mohammad Abdul Qayum

This study addresses the critical challenge of modeling and mapping urban air quality to ascertain pollutant concentrations in unmonitored locations. The advent of low-cost sensors, particularly those deployed in vehicular networks,…

Low-cost miniaturised sensors offer significant advantage to monitor the environment in real-time and accurately. The area of air quality monitoring has attracted much attention in recent years because of the increasing impacts on the…

Systems and Control · Electrical Eng. & Systems 2025-02-12 Thomas Johnson , Kieran Woodward

Environmental Protection Agency (EPA) air quality (AQ) monitors, the gold standard for measuring air pollutants, are sparsely positioned across the US due to their costliness. Low-cost sensors (LCS) are increasingly being used by the public…

Plausibility of data from networks of low-cost measurement devices is a growing and important contentious issue. Informal networks of low-cost devices have particularly come to prominence for air quality monitoring. The contentious point is…

Applications · Statistics 2019-10-09 David E Williams

Low-cost particulate matter sensors (LCS) are an important source of air quality data, improving the spatial and temporal resolution of data gathered by sparsely placed official monitoring stations. Their readings, however, are subject to…

Atmospheric and Oceanic Physics · Physics 2024-03-15 Robert Blaga

Low-cost sensors (LCS) are increasingly being used to measure fine particulate matter (PM2.5) concentrations in cities around the world. One of the most commonly deployed LCS is the PurpleAir with about 15,000 sensors deployed in the United…

Constructing high resolution air pollution maps at lower cost is crucial for sustainable city management and public health risk assessment. However, traditional fixed-site monitoring lacks spatial coverage, while mobile low-cost sensors…

Machine Learning · Computer Science 2025-03-18 Rui Xu , Dawen Yao , Yuzhuang Pian , Ruhui Cao , Yixin Fu , Xinru Yang , Ting Gan , Yonghong Liu

Low-cost sensors (LCS) for measuring air pollution are increasingly being deployed in mobile applications but questions concerning the quality of the measurements remain unanswered. For example, what is the best way to correct LCS data in a…

Real-time air pollution monitoring is a valuable tool for public health and environmental surveillance. In recent years, there has been a dramatic increase in air pollution forecasting and monitoring research using artificial neural…

Machine Learning · Computer Science 2022-11-11 Chen Lin , Safoora Yousefi , Elvis Kahoro , Payam Karisani , Donghai Liang , Jeremy Sarnat , Eugene Agichtein

The quality of air is closely linked with the life quality of humans, plantations, and wildlife. It needs to be monitored and preserved continuously. Transportations, industries, construction sites, generators, fireworks, and waste burning…

Machine Learning · Computer Science 2023-04-20 Amisha Gangwar , Sudhakar Singh , Richa Mishra , Shiv Prakash

Ambient air pollution poses significant health and environmental challenges. Exposure to high concentrations of PM$_{2.5}$ have been linked to increased respiratory and cardiovascular hospital admissions, more emergency department visits…

Applications · Statistics 2026-02-27 Zeinab Mohamed , Wenlong Gong

Air pollution stands as the fourth leading cause of death globally. While extensive research has been conducted in this domain, most approaches rely on large datasets when it comes to prediction. This limits their applicability in…

Machine Learning · Computer Science 2024-01-10 Mulomba Mukendi Christian , Hyebong Choi

With the intensification of global climate change, accurate prediction of air quality indicators, especially PM2.5 concentration, has become increasingly important in fields such as environmental protection, public health, and urban…

Machine Learning · Computer Science 2025-08-18 Zicheng Guo , Shuqi Wu , Meixing Zhu , He Guandi

Air pollution in urban areas has severe consequences for both human health and the environment, predominantly caused by exhaust emissions from vehicles. To address the issue of air pollution awareness, Air Pollution Monitoring systems are…

Machine Learning · Computer Science 2023-07-04 Hemanth Karnati

This paper presents an engine able to forecast jointly the concentrations of the main pollutants harming people's health: nitrogen dioxyde (NO2), ozone (O3) and particulate matter (PM2.5 and PM10, which are respectively the particles whose…

Machine Learning · Computer Science 2020-06-17 Antoine Alléon , Grégoire Jauvion , Boris Quennehen , David Lissmyr
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